Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/54469
Title: Multi-Channel satellite image analysis using a variational approach
Authors: Alvarez, L. 
Castaño, C. A.
García, M.
Krissian, K.
Mazorra, L. 
Salgado, A.
Sánchez, J. 
UNESCO Clasification: 120601 Construcción de algoritmos
120602 Ecuaciones diferenciales
220990 Tratamiento digital. Imágenes
Keywords: Optic Flow Computation
Cloud-Motion Winds
Classification
Tracking
Fields, et al
Issue Date: 2008
Publisher: 0033-4553
Journal: Pure and Applied Geophysics 
Abstract: Currently, meteorological satellites provide multichannel image sequences including visible, temperature and water vapor channels. Based on a variational approach, we propose mathematical models to address some of the usual challenges in satellite image analysis such as: (i) the estimation and smoothing of the cloud structures by decoupling them into different layers depending on their altitudes, (ii) the estimation of the cloud structure motion by combining information from all the channels, and (iii) the 3D visualization of both the cloud structure and the estimated displacements. We include information of all the channels in a single variational motion estimation model. The associated Euler-Lagrange equations yield to a nonlinear system of partial differential equations that we solve numerically using finite-difference schemes. We illustrate the performance of the proposed models with numerical experiments on two multichannel satellite sequences of the North Atlantic, one of them from the Hurricane Vince. Based on a realistic synthetic ground truth motion, we show that our multichannel approach overcomes the single channel estimation for both the average Euclidean and angular errors.
URI: http://hdl.handle.net/10553/54469
ISSN: 0033-4553
DOI: 10.1007/s00024-008-0347-3
Source: Pure and Applied Geophysics[ISSN 0033-4553],v. 165, p. 1071-1093
Appears in Collections:Actas de congresos
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